In this course, you will analyze and apply essential design principles to your Tableau visualizations. This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization. You will define and examine the similarities and differences of exploratory and explanatory analysis as well as begin to ask the right questions about what’s needed in a visualization. You will assess how data and design work together, including how to choose the appropriate visual representation for your data, and the difference between effective and ineffective visuals. You will apply effective best practice design principles to your data visualizations and be able to illustrate examples of strategic use of contrast to highlight important elements. You will evaluate pre-attentive attributes and why they are important in visualizations. You will exam the importance of using the "right" amount of color and in the right place and be able to apply design principles to de-clutter your data visualization.

審閱

NN

The course is not only focusing on the Tableau project, but also discussing key notes that need applying to make visualization become more effective. That is great course! Thanks!

UN

Jun 14, 2019

Filled StarFilled StarFilled StarFilled StarFilled Star

Good introduction to Tableau essentials. I enjoy the step by step instructions on creating analytics in Tableau. Receiving a year long subscritpion to the license is also AMAZING

從本節課中

Getting Started in Effective and Ineffective Visuals

Welcome to this first module where we are going to start you off with background information about how the human brain perceives the world and then you will discover effective and ineffective visuals. By the end of this module, you will be able to recognize how the brain relates to visual design. You will know the difference between cognitive versus perceptual design. You will learn the various visualization options offered by Tableau and some of their advantages and disadvantages. You will discuss why how good ethical practices play in designing visualizations. You will also start to examine ineffective visualizations and learn how to improve them.

教學方

Govind Acharya

Hunter Whitney

腳本

[MUSIC] Welcome back. In the last lesson, we saw how a basic awareness of our brain's strengths and limitations can be a useful part of the visualizers toolkit. This approach extends beyond pop-out effects to higher order considerations. As a data visualization designer, you need to think about using design elements to help people both perceive and to think about data. So in this lesson, we'll consider two fundamental systems of the brain that will have a bearing on design. Let's get started. Hi, in a previous lesson, we briefly touch in how visual encoding provides basic building blocks from making data more immediately perceptible to people, but perception is only part of the story. As a data visualization designer, you should also consider how your designs can help people make clear, accurate interpretations and gain useful insights based on what they see. Nobel prize winning psychologist Daniel Kahneman suggested that there are two fundamental systems that drive how we think and make judgments. As a data visualization designer, your job is to leverage both of them. The first system involves more automatic and immediate perception, such as noticing an unusual pattern of movement in the bushes. This is where visual encoding and things like Gestalt Principles which will be touched on a future lesson come into play. The second system above slower and more deliberate cognition. That is thinking about the meaning of certain sensory cues. What interpretations and questions should arise from a particular visual pattern. For instance, an analyst might immediately notice a single dot sitting alone but nearby to a cluster of other dots in a scatter plot. That's system 1. If the analysts spent a few moments considering a bad data as a meaningful outlier with further investigation, that would be system two. Confronting a large set of multidimensional data can be overwhelming for any of us. Your task is to create a way to encode that data so that they can be put together like letters into words or like Lego bricks into meaningful patterns that work with both or perceptual and cognitive systems. Making good choices for combining various visual encoding options. For effect, the visualizations is both an art and a science. Here's a simple example using color and shape. Now you may find that color pops out more than shape but the combination of the two encoding options allows for a more detailed story to emerge from the pattern. How much more can be added to show even more informational depth without overloading the viewer and obscuring the meaning, well those are going to be decisions you going to need to make. In a trade off of speed versus accuracy of perception speed often wins, for the reasons noted earlier in this lesson. In the case of the unknown movement in the bushes, the value of instant action outweighed accuracy. From a survival point of view, it was better to react quickly even if there are many false alarms in the process. The brain relies on some shortcuts and assumptions to help make our perception rapid, and that's a key to good data visualizations. But some of the same mental shortcuts can also create false interpretations and provide challenges and present challenges for visualization designs. For example, do you see the gradient in that gray bar in the middle of the larger gray box? In fact, there isn't a gradient, but you immediately perceive it as having a gradient because of the background context. Even if you know it's not there, you've probably can't help but see that gradient anyway. That's just how your brain works. As designers, you should be aware of what effect your design decisions what might have on users' perceptions and their resulting interpretations. As we have seen, data visualization is as much about the brain and how it works as it is about colors, lines and shapes. In later lessons, we will explore design strategies that draw from working with systems one and two. As you go through the rest of this course, please keep these ideas in the back of your mind as they will lead you down the path of good design principles for visualization. Until next time.